Skip to main content
DA / EN

PhD Projects

Ongoing PhD projects:

 

PhD student Tim Wächter

Dynamic Evacuation Route Guidance in the Intelligent Building

October 2023 - ongoing

Public buildings, such as office buildings, hospitals, train stations, and airports, are becoming increasingly larger and more complex. Consequently, more and more people work in these facilities. Therefore, it is very important that buildings have a high level of safety.
The goal of this dissertation is to explore innovative ways to combine fire protection, building automation and modern user interfaces through interdisciplinary research to improve building evacuation procedures during emergencies.
Currently, evacuation routes are planned as static escape route plans and posted in buildings. As a result, static escape routes are incapable of responding to dynamic and temporary events within the building, which is essential in a fire emergency where the escape route should guide individuals away from danger.

This work is divided into three subgoals:

  1. Development of a virtual 3D environment for the simulation and evaluation of escape route algorithms.
  2. Development and evaluation of dynamic building evacuation strategy algorithms.
  3. Development and evaluation of suitable user guidance interfaces for dynamic evacuation.
 

PhD student Alessandro Pisanu

Agile at scale: the case of Additive Design & Manufacturing at the LEGO Group

October 2023 - ongoing

This project is financed by and developed at the LEGO Group.

Introduction

Retaining competitive advantage is increasingly challenging due to rapid knowledge generation. Companys experiment with various innovation management approaches, but their applicability is influenced by several factors such as their complexity and structure, the physicality of the products under development, the culture, the types of workflows and so on. 

Goals

The main objective of this research is to understand what are the factors that play a role in the applicability of hybrid agile practices, for the case of a team that carries out R&D activities and operations, while developing cyber-physical products through collaborative innovation. We want to understand how a team can work flexibly while carrying out activities that are typically managed with traditional methods. Moreover, we want to define how a fast-growing team can scale and become structured while staying open to fast-changing requirements. 

Industrial use case and expected contribution

This research focuses on the LEGO Group's Additive Design & Manufacturing department, which has seen substantial growth due to its innovation and portfolio diversification. The challenge is to remain agile while managing growth and complexity. Combining agile and structured methods can be beneficial, but their effectiveness varies. The study will explore the best framework for managing the LEGO Group’s innovation and technology portfolio and supporting operations.

 

 


PhD student Thore Uwe Aye

Dynamic Operations and Demand Forecasting for Agile and Resilient Inventory Management in a Multiple-Buyer, Multiple-Supplier Landscape

November 2022 - ongoing

The retail landscape has undergone significant transformation, with demand forecasting emerging as a crucial component for efficient supply chain management. The increasing pressure on global supply chains, accentuated by rapid shifts in consumer behavior and technological advancements, poses unprecedented challenges for businesses. This PhD project aims to develop a comprehensive framework for dynamic operations and demand forecasting to support agile and resilient inventory management in complex, multi-buyer, multi-supplier environments.

The research focuses on several key areas:
1. Mapping the interrelated processes between sales, demand, and inventory.
2. Identifying critical sales factors and demand forecasting models that enhance dynamic inventory management.
3. Proposing a combined framework for dynamic forecasting and agile inventory planning.
4. Analyzing different scenarios to understand the interconnection between sales history, demand forecasting, and inventory planning.

The methodology includes a systematic literature review, the development of a novel framework, and its application in a case study. This research aims to create agile and resilient supply chains that can adapt to rapid market changes and unexpected disruptions, helping companies maintain optimal stock levels.
The integration of technologies such as machine learning, artificial intelligence, and big data analytics is pivotal. These technologies enhance the processing and analysis of vast datasets, enabling more accurate and dynamic decision-making. The project also balances short-term tactical and long-term strategic forecasting, incorporating both endogenous and exogenous factors to improve forecasting accuracy and operational performance.

For further information, please contact Thore Uwe Aye, thoreaye@iti.sdu.dk, or Elias Ribeiro da Silva, elias@iti.sdu.dk.

 

Completed PhD projects:

 

PhD Jesper Puggaard de Oliveira Hansen 

Adaptable automation driven by simulation and digital twins (MADE)

June 2020 - February 2024

This project is supported by MADE – Manufacturing Academy Denmark and Siemens A/S.

The goal is to research the value chain from product development to operation and how to use simulation and digital twin to increase adaptability for design, planning and operation of automation solutions. The focus will be from machine builder to the end customer where innovative adaptable machine modules will be designed and integrated into adaptable production cells based at specifications from the end user.

The goal is to develop an integrated framework, where virtual models are linked to physical counterparts. In the collaboration between universities and Siemens, innovative use of the PLM and automation tools will be applied and further developed, leading to real demonstrators in the laboratory environment as well as at the case company Velux.

For further information, please contact  Jesper Puggaard de Oliveira Hansen, jesperp@iti.sdu.dk or Arne Bilberg, abi@iti.sdu.dk


PhD Christian Petersson Nielsen

Matrix‐Structured Manufacturing Systems: From Design to Operations

August 2019 - April 2023

In recent years, the need for more flexible manufacturing systems has increased. This is caused by the consumers’ increasing demand for more individualized products at a low price point. To achieve this, the manufacturing companies must be able to produce products with a wide variety and high production volume. This requires a multitude of flexibility types, such as product flexibility, control program flexibility, material handling flexibility, and similar. One of the manufacturing system paradigms that address these types of flexibility is Matrix‐Structured Manufacturing Systems, also often denoted Matrix Production. 

Matrix‐Structured Manufacturing Systems consist of reconfigurable, standardized work cells, typically scattered in a matrix pattern, with a flexible non‐linear material flow between the work cells. The current literature on this type of manufacturing system is primarily focused on the design of the manufacturing system and its critical components of it. This means that the current literature does not address the transition from design to operations of this manufacturing system. This research gap is addressed in the PhD thesis, which investigates:

1) How Matrix‐Structured Manufacturing Systems facilitate flexibility,
2) How to design Matrix‐Structured Manufacturing Systems, and
3) How to control Matrix‐Structured Manufacturing Systems

These research questions are answered using respectively a systematic literature review, a laboratory case study, and two company case studies. The results from these methodologies yield, among others, two approaches to design both the work cells and products within this type of manufacturing system. Furthermore, to fully benefit from the increased flexibility from this manufacturing system, a control system architecture targeted Matrix‐Structured Manufacturing Systems is furthermore developed.

Based on the results from the research questions, Matrix‐Structured Manufacturing Systems are discussed in relation to a supply chain perspective. This perspective pays special attention to the resilience that is both enabled and required, when implementing this type of manufacturing system. Additionally, a sustainability perspective is discussed in connection with the supply chain perspective. Finally, Matrix‐Structured Manufacturing Systems are discussed as an enabler for new business opportunities, such as Manufacturing‐as‐a‐Service. With this foundation, a discussion and reflection on Matrix‐Structured Manufacturing Systems as a manufacturing system of the future is presented.

SDU Technology Entrepreneurship and Innovation University of Southern Denmark

  • Alsion 2
  • Sønderborg - DK-6400
  • Phone: +45 6550 1690
  • Fax: +45 6550 1635

Last Updated 08.08.2024